DYNASTI—Dynamic Multiple RPL Instances for Multiple IoT Applications in Smart City

Internet of Things (IoT) is evolving to multi-application scenarios in smart cities, which demand specific traffic patterns and requirements. Multi-applications share resources from a single multi-hop wireless networks, where smart devices collaborate to send collected data over a Low-Power and Lossy Networks (LLNs). Routing Protocol for LLNs (RPL) emerged as a routing protocol to be used in IoT scenarios where the devices have limited resources. Instances are RPL mechanisms that play a key role in order to support the IoT scenarios with multiple applications, but it is not standardized yet. Although there are related works proposing multiple instances in RPL on the same IoT network, those works still have limitations to support multiple applications. For instance, there is a lack of flexibility and dynamism in management of multiple instances and service differentiation for applications. In this context, the goal of this work is to develop a solution called DYNAmic multiple RPL instanceS for multiple ioT applicatIons (DYNASTI), which provides more dynamism and flexibility by managing multiple instances of RPL. As a result of this, the traffic performance of multiple applications is enhanced through the routing, taking into consideration the distinct requirements of the applications. In addition, DYNASTI enables the support of sporadic applications as well as the coexistence between regular and sporadic applications. DYNASTI achieved results that demonstrate a significant improvement in reducing the number of control messages, which resulted in increased packet received, decreased end-to-end delay, reduced energy consumption, and an improvement in service differentiation to multiple applications.

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Dynamic Traffic Prediction with Adaptive Sampling for 5G HetNet IoT Applications

Wireless Communications and Mobile Computing ◽

10.1155/2019/4687272 ◽

2019 ◽

Vol 2019 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Shuangli Wu ◽

Wei Mao ◽

Cong Liu ◽

Tao Tang

Keyword(s):

Adaptive Sampling ◽

Control Function ◽

Smart Cities ◽

Video Stream ◽

Traffic Load ◽

Traffic Prediction ◽

Traffic Patterns ◽

Linear Predictor ◽

Iot Applications ◽

The Internet Of Things

Due to the proliferation of global monitoring sensors, the Internet of Things (IoT) is widely used to build smart cities and smart homes. 5G HetNets play an important role in the IoT video stream. This paper proposes an improved Call Session Control Function (CSCF) scheme. The improved CSCF server contains additional modules to facilitate IoT traffic prediction and resource reservation. We highlight traffic prediction in this work and develop a compressed sensing based linear predictor to catch the traffic patterns. Experimental results justify that our proposed scheme can forecast the traffic load with high accuracy but low sampling overhead.

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Mobility Aware RPL (MARPL): Providing Mobility Support for RPL Protocol

10.5753/sbrc.2019.7361 ◽

2019 ◽

Author(s):

Vinícius De Figueiredo Marques ◽

Janine Kniess

Keyword(s):

Low Power ◽

Routing Protocol ◽

Mobile Node ◽

Node Mobility ◽

Lossy Networks ◽

Detection Mechanism ◽

Mobility Support ◽

Packet Delivery ◽

Iot Applications ◽

Overall Performance

Low Power and Lossy Networks (LLNs) is a common type of wireless network in IoT applications. LLN communication patterns usually requires an efficient routing protocol. The IPv6 Routing Protocol for Low-Power and Lossy Network (RPL) is considered to be a possible standard routing protocol for LLNs. However, RPL was developed for static networks and node mobility decreases RPL overall performance. These are the purposes of the Mobility Aware RPL (MARPL), presented in this paper. MARPL provides a mobility detection mechanism based on neighbor variability. Performance evaluation results on the Cooja Simulator confirm the effectiveness of MARPL regarding link disconnection prevention, packet delivery rate and fast mobile node topology reconnection with low overhead impact when compared to other protocols.

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Performance Evaluation of Routing Metrics in the LOADng Routing Protocol

Journal of Communications Software and Systems ◽

10.24138/jcomss.v13i2.376 ◽

2017 ◽

Vol 13 (2) ◽

pp. 87 ◽

Cited By ~ 3

Author(s):

Jose V. V. Sobral ◽

Joel J. P. C. Rodrigues ◽

Neeraj Kumar ◽

Chunsheng Zhu ◽

Raja W. Ahmad

Keyword(s):

Routing Protocol ◽

Network Performance ◽

Ad Hoc ◽

Average Energy ◽

Delivery Ratio ◽

Traffic Patterns ◽

Routing Metric ◽

Lossy Networks ◽

Routing Metrics ◽

Average Latency

LOADng (Lightweight On-demand Ad hoc Distance-vector Routing Protocol - Next Generation) is an emerging routing protocol that emerged as an alternative to RPL (IPv6 Routing Protocol for Low power and Lossy Networks). Although some work has been dedicated to study LOADng, these works do not analyze the performance of this protocol with different routing metrics. A routing metric is responsible for defining values for paths during the route creation process. Moreover, based on these metrics information a routing protocol will select the path to forward a message. Thus, this work aims to realize a performance assessment study considering different routing metrics applied to LOADng. The scenarios under study consider different traffic patterns and network sizes. The routing metrics are evaluated considering the packet delivery ratio, average energy spent per bit delivered, average latency, and number of hops. The results reveals that routing metrics used by this protocol may influence (directly) the network performance.

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Detection and Mitigation of RPL Rank and Version Number Attacks in Smart Internet of Things

10.20944/preprints202007.0476.v1 ◽

2020 ◽

Author(s):

Zahrah A. Almusaylim ◽

Abdulaziz Alhumam ◽

Wathiq Mansoor ◽

Pushpita Chatterjee ◽

Noor Zaman Jhanjhi

Keyword(s):

Internet Of Things ◽

Routing Protocol ◽

Smart Cities ◽

Real Life ◽

Average Energy ◽

Delivery Ratio ◽

Lossy Networks ◽

Data Packets ◽

And Performance ◽

Average Energy Consumption

The rapid growth of the smart Internet of Things (IoT) and massive propagation of wireless technologies revealed the recent opportunities for development in various domains of real life such as smart cities and E-Health applications. A slight defense against different forms of attacks is offered for the current secure and lightweight Routing Protocol for Low Power and Lossy Networks (RPL) of IoT resource-constrained devices. Data packets are highly likely to be exposed while transmitting them during data packets routing. The RPL rank and version number attacks, which are two forms of RPL attacks, can have critical consequences for RPL networks. The studies conducted on these attacks have several security defects and performance shortcomings. The research proposes a Secure RPL Routing Protocol (SRPL-RP) for rank and version number attacks. It mainly detects, mitigates and isolates attacks in the RPL networks. The detection is based on a comparison of ranks strategy. The mitigation uses threshold and attacks status tables, and the isolation adds them to a blacklist table and alerts relevant nodes to skip them. SRPL-RP supports diverse types of network topologies and is comprehensively analyzed with multiple studies such as Standard RPL with Attacks, SBIDS and RPL+ Shield. The analysis results showed that the SRPL-RP achieves great improvements with Packet Delivery Ratio (PDR) of 98.48%, control message value of 991 packets/second, and average energy consumption of 1231.75 joules. It provides a better accuracy rate with 98.17% under the attacks.

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History-based consistency algorithm for the trickle-timer with low-power and lossy networks

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v11i3.pp2569-2576 ◽

2021 ◽

Vol 11 (3) ◽

pp. 2569

Author(s):

Firas A. Albalas ◽

Haneen Taamneh ◽

Wail E. Mardini

Keyword(s):

Power Consumption ◽

Low Power ◽

Routing Protocol ◽

Convergence Time ◽

Limited Resources ◽

The Internet ◽

Delivery Ratio ◽

Lossy Networks ◽

Main Components ◽

The Internet Of Things

Recently, the internet of things (IoT) has become an important concept which has changed the vision of the Internet with the appearance of IPv6 over low power and lossy networks (6LoWPAN). However, these 6LoWPANs have many drawbacks because of the use of many devices with limited resources; therefore, suitable protocols such as the Routing Protocol for low power and lossy networks (RPL) were developed, and one of RPL's main components is the trickle timer algorithm, used to control and maintain the routing traffic frequency caused by a set of control messages. However, the trickle timer suffered from the short-listen problem which was handled by adding the listen-only period mechanism. This addition increased the delay in propagating transmissions and resolving the inconsistency in the network. However, to solve this problem we proposed the history based consistency algorithm (HBC), which eliminates the listen-only period based on the consistency period of the network. The proposed algorithm showed very good results. We measured the performance of HBC trickle in terms of convergence time; which was mainly affected, the power consumption and the packet delivery ratio (PDR). We made a comparison between the original trickle timer, the E-Trickle, the optimized trickle and our HBC trickle algorithm. The PDR and the power consumption showed in some cases better results under the HBC trickle compared to other trickle timers and in other cases the results were very close to the original trickle indicating the efficiency of the proposed trickle in choosing optimal routes when sending messages.

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Congestion Control and Traffic Differentiation for Heterogeneous 6TiSCH Networks in IIoT

Sensors ◽

10.3390/s20123508 ◽

2020 ◽

Vol 20 (12) ◽

pp. 3508

Author(s):

Hossam Farag ◽

Patrik Österberg ◽

Mikael Gidlund

Keyword(s):

Congestion Control ◽

Routing Protocol ◽

Network Performance ◽

Heavy Traffic ◽

Service Differentiation ◽

Routing Metric ◽

Lossy Networks ◽

Heavy Load ◽

Packet Delivery ◽

Critical Data

The Routing Protocol for Low power and lossy networks (RPL) has been introduced as the de-facto routing protocol for the Industrial Internet of Things (IIoT). In heavy load scenarios, particular parent nodes are likely prone to congestion, which in turn degrades the network performance, in terms of packet delivery and delay. Moreover, there is no explicit strategy in RPL to prioritize the transmission of different traffic types in heterogeneous 6TiSCH networks, each according to its criticality. In this paper, we address the aforementioned issues by introducing a congestion control and service differentiation strategies to support heterogeneous 6TiSCH networks in IIoT applications. First, we introduce a congestion control mechanism to achieve load balancing under heavy traffic scenarios. The congestion is detected through monitoring and sharing the status of the queue backlog among neighbor nodes. We define a new routing metric that considers the queue occupancy when selecting the new parent node in congestion situations. In addition, we design a multi-queue model to provide prioritized data transmission for critical data over the non-critical ones. Each traffic type is placed in a separate queue and scheduled for transmission based on the assigned queue priority, where critical data are always transmitted first. The performance of the proposed work is evaluated through extensive simulations and compared with existing work to demonstrate its effectiveness. The results show that our proposal achieves improved packet delivery and low queue losses under heavy load scenarios, as well as improved delay performance of critical traffic.

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CoAR: Congestion-Aware Routing Protocol for Low Power and Lossy Networks for IoT Applications

Sensors ◽

10.3390/s18113838 ◽

2018 ◽

Vol 18 (11) ◽

pp. 3838 ◽

Cited By ~ 19

Author(s):

Khadak Bhandari ◽

A. Hosen ◽

Gi Cho

Keyword(s):

Low Power ◽

Monitoring System ◽

Routing Protocol ◽

Selection Process ◽

Lossy Networks ◽

Detection Mechanism ◽

Iot Applications ◽

Wide Range ◽

Parent Node ◽

Congestion Aware

The IPv6 routing protocol for low power and lossy networks (RPL) was designed to satisfy the requirements of a wide range of Internet of Things (IoT) applications, including industrial and environmental monitoring. In most scenarios, different from an ordinary environment, the industrial monitoring system under emergency scenarios needs to not only periodically collect the information from the sensing region, but also respond rapidly to some unusual situations. In the monitoring system, particularly when an event occurs in the sensing region, a surge of data generated by the sensors may lead to congestion at parent node as data packets converge towards the root. Congestion problem degrades the network performance that has an impact on quality of service. To resolve this problem, we propose a congestion-aware routing protocol (CoAR) which utilizes the selection of an alternative parent to alleviate the congestion in the network. The proposed mechanism uses a multi-criteria decision-making approach to select the best alternative parent node within the congestion by combining the multiple routing metrics. Moreover, the neighborhood index is used as the tie-breaking metric during the parent selection process when the routing score is equal. In order to determine the congestion, CoAR adopts the adaptive congestion detection mechanism based on the current queue occupancy and observation of present and past traffic trends. The proposed protocol has been tested and evaluated in different scenarios in comparison with ECRM and RPL. The simulation results show that CoAR is capable of dealing successfully with congestion in LLNs while preserving the required characteristics of the IoT applications.

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ARTIFICIAL INTELLIGENCE AS A SERVICE IN DISTRIBUTED MULTI ACCESS EDGE COMPUTING ON 5G EXTRACTING DATA USING IOT AND INCLUDING AR/VR FOR REAL-TIME REPORTING

INFORMATION TECHNOLOGY IN INDUSTRY ◽

10.17762/itii.v9i1.220 ◽

2021 ◽

Vol 9 (1) ◽

pp. 912-931

Author(s):

Pavan Madduru

Keyword(s):

Cloud Computing ◽

Internet Of Things ◽

Virtual Machines ◽

Smart Cities ◽

Assistive Technologies ◽

Edge Computing ◽

Smart Devices ◽

The Internet ◽

Iot Applications ◽

The Internet Of Things

To meet the growing demand for mobile data traffic and the stringent requirements for Internet of Things (IoT) applications in emerging cities such as smart cities, healthcare, augmented / virtual reality (AR / VR), fifth-generation assistive technologies generation (5G) Suggest and use on the web. As a major emerging 5G technology and a major driver of the Internet of Things, Multiple Access Edge Computing (MEC), which integrates telecommunications and IT services, provides cloud computing capabilities at the edge of an access network. wireless (RAN). By providing maximum compute and storage resources, MEC can reduce end-user latency. Therefore, in this article we will take a closer look at 5G MEC and the Internet of Things. Analyze the main functions of MEC in 5G and IoT environments. It offers several core technologies that enable the use of MEC in 5G and IoT, such as cloud computing, SDN / NFV, information-oriented networks, virtual machines (VMs) and containers, smart devices, shared networks and computing offload. This article also provides an overview of MEC's role in 5G and IoT, a detailed introduction to MEC-enabled 5G and IoT applications, and future perspectives for MEC integration with 5G and IoT. Additionally, this article will take a closer look at the MEC research challenges and unresolved issues around 5G and the Internet of Things. Finally, we propose a use case that MEC uses to obtain advanced intelligence in IoT scenarios.

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Detection and Mitigation of RPL Rank and Version Number Attacks in the Internet of Things: SRPL-RP

Sensors ◽

10.3390/s20215997 ◽

2020 ◽

Vol 20 (21) ◽

pp. 5997

Author(s):

Zahrah A. Almusaylim ◽

NZ Jhanjhi ◽

Abdulaziz Alhumam

Keyword(s):

Internet Of Things ◽

Routing Protocol ◽

Smart Cities ◽

Real Life ◽

Average Energy ◽

The Internet ◽

Delivery Ratio ◽

Lossy Networks ◽

Average Energy Consumption ◽

The Internet Of Things

The rapid growth of the Internet of Things (IoT) and the massive propagation of wireless technologies has revealed recent opportunities for development in various domains of real life, such as smart cities and E-Health applications. A slight defense against different forms of attack is offered for the current secure and lightweight Routing Protocol for Low Power and Lossy Networks (RPL) of IoT resource-constrained devices. Data packets are highly likely to be exposed in transmission during data packet routing. The RPL rank and version number attacks, which are two forms of RPL attacks, can have critical consequences for RPL networks. The studies conducted on these attacks have several security defects and performance shortcomings. In this research, we propose a Secure RPL Routing Protocol (SRPL-RP) for rank and version number attacks. This mainly detects, mitigates, and isolates attacks in RPL networks. The detection is based on a comparison of the rank strategy. The mitigation uses threshold and attack status tables, and the isolation adds them to a blacklist table and alerts nodes to skip them. SRPL-RP supports diverse types of network topologies and is comprehensively analyzed with multiple studies, such as Standard RPL with Attacks, Sink-Based Intrusion Detection Systems (SBIDS), and RPL+Shield. The analysis results showed that the SRPL-RP achieved significant improvements with a Packet Delivery Ratio (PDR) of 98.48%, a control message value of 991 packets/s, and an average energy consumption of 1231.75 joules. SRPL-RP provided a better accuracy rate of 98.30% under the attacks.

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Compressive Sensing-Based IoT Applications: A Review

Journal of Sensor and Actuator Networks ◽

10.3390/jsan7040045 ◽

2018 ◽

Vol 7 (4) ◽

pp. 45 ◽

Cited By ~ 15

Author(s):

Hamza Djelouat ◽

Abbes Amira ◽

Faycal Bensaali

Keyword(s):

Compressive Sensing ◽

Smart Cities ◽

High Energy ◽

Cooperative Transmission ◽

Smart Devices ◽

Signal Acquisition ◽

Real World Data ◽

Battery Lifetime ◽

Iot Applications ◽

Self Powered

The Internet of Things (IoT) holds great promises to provide an edge cutting technology that enables numerous innovative services related to healthcare, manufacturing, smart cities and various human daily activities. In a typical IoT scenario, a large number of self-powered smart devices collect real-world data and communicate with each other and with the cloud through a wireless link in order to exchange information and to provide specific services. However, the high energy consumption associated with the wireless transmission limits the performance of these IoT self-powered devices in terms of computation abilities and battery lifetime. Thus, to optimize data transmission, different approaches have to be explored such as cooperative transmission, multi-hop network architectures and sophisticated compression techniques. For the latter, compressive sensing (CS) is a very attractive paradigm to be incorporated in the design of IoT platforms. CS is a novel signal acquisition and compression theory that exploits the sparsity behavior of most natural signals and IoT architectures to achieve power-efficient, real-time platforms that can grant efficient IoT applications. This paper assesses the extant literature that has aimed to incorporate CS in IoT applications. Moreover, the paper highlights emerging trends and identifies several avenues for future CS-based IoT research.

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